Category Archives: Investment

The solar industry is going through an unprecedented amount of change, and opportunities to leverage its success are bigger than ever. In the last fifteen years, solar energy has expanded from a niche technology to an important asset class. According to a study by Bloomberg New Energy Finance, from 2004 to 2015, over a trillion dollars of capital has been deployed in solar project, at a compounded annual growth rate of 27%.

At Anthemis, our investment strategy has always been to focus on companies that pioneer technology-driven structural changes to the financial services industry. In our view, emerging financial markets need both a shared data language and risk appreciation to become prevalent asset classes.

Until now, these two critical components have been missing in the solar energy market. kWh Analytics was founded to bring new data to the solar industry. From inception, kWh has built a unique industry database and toolset to help investors understand and improve solar investment performance. The company is now launching a solar production insurance product, Powerlock, to protect asset owners and debt providers. kWh is already working with some of the biggest names in the asset management space as well as global insurance carriers.

Despite the huge growth of the solar energy sector, the industry is still a tiny fraction of global electricity production. With the cost of solar energy production declining, and an increasing understanding of the necessity to change our energy production mix, the solar energy market is poised for growth.

Richard Matsui and the kWh team have formidable experience in the solar energy market, having worked in the industry since its infancy. Anthemis is excited to support them by leading their Series A as they continue developing solutions that provide the necessary components to accelerate growth in this expanding asset class. Not only do we believe solar is a great business opportunity, it is also part of an important problem to tackle.

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Looking at 2016 with the experience of the past 7 years in financial services. it will be a pivotal year for financial services. In many ways we are coming to the end of a phase, that started with the world‘s the most important financial crisis since 1929. The FED hike is upon us, after having experienced one of the most destructive slow downs, of which the effects are still very much acute through the world. While banks are still experiencing the effect of the crisis notably through restrictive regulation and a continuing string of financial scandals, their public messaging is one of innovation and change. For the raft of new players in financial services, the funding environment has never been as good and some striking successes are showing the way forward. A new wave of technology, from blockchain to AI and omnipresent sensors is shaping a new world (hopefully not brave).

2016 will see a strong competition in the pure banking space. In Europe especially, a crop of new banks and alternative banks will push strongly into the market. European digital banks such as Fidor are expanding beyond their core market.The UK regulator’s move to lowering the barrier to entry in becoming a bank will come to reality with Atom Bank, Tandem, (…) establishing themselves as a brand to customers. Alternative solutions based on prepaid born in various european countries are also expanding beyond borders, with SEPA as a core foundation to propose bank like services. With PSD2 looming, traditional banks have the opportunity / incentive to more easily expand collaboratively with startups.

What about the alternative lenders, roboadvisors and other digital financial services players? Having spent the last few years building a trusted brand as well as consolidating a customer base, it is highly possible they will start leveraging this to expand horizontally into other markets, whether collaboratively or by launching their own services. For example, blended remittance and multi currencies current accounts are highly complementary services for clients with attachments to multiple countries.

This collaboration between emerging players will most likely extend beyond end customers, towards balance sheet management, especially for emerging banks looking at matching assets to their new found deposits. Looking beyond the pure European and US context, in a developing world that is increasingly interconnected, via diasporas and large economic regions, the winning platform of the coming decades appears to be the messaging platforms: Wechat, Line, Facebook Messenger and WhatsApp are all showing significant growth, engagement and increasingly financial services integration. 2016 may be the year where we will see Facebook becoming more integrated with financial services, leading with seamless blending of messaging, commerce and payment first and potentially P2P transactions next.

If 2015 was the awakening of the entrepreneurs, investors and incumbents to the potential disruption of insurance by digital first players, 2016 may well shape up to be the coming of more true game changing challengers in the space. In reality, most of the investment and company creation has gone through changing distribution to digital means, focusing mainly on two main trends: the modernization of broker first markets, such as the German or Swiss markets (following the UK market) where digital acquisition is seen as a cost efficient, scalable way to attract customers and the reorganization of health insurance in the US market following the Obamacare reform. What is maybe more interesting is the coming wave of startups looking to challenge the core business model of insurance companies, an early example of which is Oscar. These new players are leveraging lower cost, scalable infrastructures, sometimes through mutual insurance mechanisms.Increasingly, a smart use of the full insurance stack including innovative insurance companies and nimble reinsurance players allows them to succeed at lower scale. Another trend that will shape up 2016 is the change from insuring people for their things to insuring their things for them partly driven by the increasing importance of the internet of things and the facts that objects are more and more blending with the underlying services they provide.

If 2014 was seemingly the year of Bitcoin, with its pricing toping above $1,000. 2015 was the year of transitioning from currency to infrastructure. 2016 will be the year of blockchains as infrastructures for smart contracts. Financial services use cases in clearing and settlement will continue to dominate the headlines with an increasing number of pilots and low scale production releases. Financial services being multi parties by definition, they are a prime market for decentralized trusted software but the use cases go well beyond pure transactional financial services and the coming year will see an increased such projects. Large scale projects are also by definition multi parties and can benefit from a smart contract infrastructure. And lets not forget the elephant in the room, our civil infrastructure which needs to reinvent itself for the digital age.

Finally, taking a longer view, it will be important to focus on two complementary trends. Artificial Intelligence and omnipresent data. Financial services core functions are based on managing capital scarcity and information asymmetry. With the amount of data increasing at high speed, notably through widespread, cheaper and more detailed sensors and the capability to process it progressing in parallel through the use of machine intelligence, the core market of financial services will be affected. The autonomous car is the perfect metaphor for it: what is the insurance market for a sensor full, crash avoiding vehicle? But similarly, what new markets will this create for financial services?

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It feels like fear around artificial intelligence is slightly receding and that the discussion has evolved toward what it can actually do now and its application in the current crop of technology companies. I, for one, welcome this new step in Machiavellianism from our machine overlords, well played, well played….

“ A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.”

Machine learning comes in various shapes but broadly there are important distinctions between:
– supervised learning, in which the computer is given example inputs and desirable outputs, with the goal for the machine to learn how to map the two.
– unsupervised learning, in which the inputs are not characterized and the machine has to learn what characteristics of the inputs are linked to the desirable outputs.

It is also important to understand that desirable outputs are effectively formulated as algorithms. They are very diverse and not only depend on the problem but also the approach taken to solve it. For example the graph below gives a good overview of potential solutions to a regression analysis problem.

So how does a machine think? Very differently from us as its input are more constrained data sets and its outputs are driven by equations. For example, this is how a computer views a picture of a cat on a carpet in order to be able to classify it as such.

It makes sense for these large players to open source a big part of their research and benefit from a broader development community. As we discussed above, an essential part of machine learning is gained from data and training, two components that remains firmly proprietary.

In Financial Services, in my mind there are short term two main cases for machine learning: one connected to the interface between humans and finance, the other to optimizing the analysis of vast pools of data.

Facebook’s experimentation with M, is a strong indication of the future interface for financial services. Whether existing banks and financial services providers have the skill-set and ability to build and train these agents is an open question. Especially as AI has a strong lock-in effect.

On the data front, one of the key use of machine learning lies first with the ability to analyze at scale and speed data that would require an army of humans. A good example is satellite data. Companies such asDescartes Labs have the ability to determine crop type in satellite pictures of fields across massive sets of information. The other use case will most likely be understanding correlations in the large pool of digital breadcrumbs that people and companies increasingly create. Trading data, Credit scoring, because of their data rich outputs are prime targets. In credit scoring, one of the key concerns will be to make sure that these self learning algorithms comply with non discrimination laws.

Increasingly, if you are working on innovation in financial services and not actively looking into machine learning, you are probably doing it wrong.

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Late last year, Anthemis invested in Eris Industries. Eris was known in the Bitcoin world for having worked on DOUG, a smart contract based replacement for the Bitcoin foundation (still an interesting concept in these Bitcoin governance days). We were attracted by the quality of the team and their vision. See my blog post at the time.

Eris Industries was one of the early companies to see the potential value of permissioned ledgers and understood the need to make the creation of distributed application accessible to most developers. But at core, Eris Industries’ passion and our enthusiasm for them come from their focus on smart contracts, pieces of code with unique attributes running on a Blockchain. Distributed applications built with smart contracts have the potential to change how corporations are built, how federated organization are run and to make contracts (such as securities in the financial services world) partly autonomous entities. In my view, its one of the most exciting space in technology, because of its potential impact across multiple industries and its longer term its potential impact in redefining how our society is working (a key aspect in Carlota Perez’s theory of technology and economic cycles). The fact that Bitcoin could go from a white paper shared on an obscure forum to what is it now is just a small example of what distributed applications could do.

However most great things don’t come from planned execution but from the creative destruction of innovation. A key driver of that is entrepreneurial endeavor, especially driven by democratized, open sources tools, one of the key fundamentals of why software is eating the world – to take Marc Andreessen’s words. For distributed applications to succeed, we need thousands and thousands of people building stuff this way and for that to happen we need tools to support them. With the Eris 0.10 platform, Eris Industries is building one of those tools, an application framework to build smart contract based, distributed software on Blockchains, any type of Blockchains. Because blockchain development is important, Eris Industries will also continue its contribution to the open source Tendermint project. Researching consensus solutions is another key driver for the success of blockchains in general (permissioned or permissionless).

Some of the key KPIs in an early technology cycle are simple: lines of code and developers:

– The Eris 0.10 is available on Github, the Eris Industries team has dedicated channels to support developers and documentation/tutorials are regularly updated. Read this series of tutorials on Solidity for example.

– Several developers have started to experiment and build on the Eris platform, from large software companies, to banks, insurers and startups. Everledger is one example.

For the blockchain industry to move beyond the newspapers headlines, consultant reports and generic {we could do that} use cases we need more code to be written. Its “interesting” to write about permissioned car access, automated securities settlement, distributed Uber competitors but its way cooler to start building these. We hope Eris Industries will be one of the key partners to do so.

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While other sectors attract more mainstream press attention (payment, retail banking), the asset management industry is also deeply affected by “software eating the world”.

Asset Class CompetitionTraditional asset management companies are increasingly facing competition on both sides of the performance scale. On the “Beta” end of the scale, ETFs are steadily becoming one of the most successful innovation in recent decades. By automatically tracking indexes, they offer investors the possibility to obtain market performance at a lower cost than a typical managed funds.

Additionally, more players are appearing making ETFs investment easier and more meaningful for private investors. Companies such as Betterment (disclosure, Anthemis is an investor & I am a customer) make investing in a diversified portfolio of ETFs easy and provide additional services such as automated rebalancing and tax optimisation.

On the other end of the scale (Alpha), access to alternative assets has become easier with the JOBS act. By lifting the ban on general solicitation and making crowdfunding easier, the JOBS act is opening access (for accredited investors for now) to the Venture Capital and Hedge Funds asset classes. Platforms such as Angelist, Seedinvest or Fundersclub (with differences in each models) are making startup investment easier to more people and are solving key pain points such as keeping cap table reasonable. In the hedge fund world, companies like Artivest are experimenting with opening up access to established funds to more accredited investors.

Other assets classes are also opening up and proving competitive. Lendingclub has provided attractive returns to individual investors who would never have had the possibility to directly invest in consumer lending with the necessary diversification. Realtymogul opens up direct access to large real estate investments.

Note: with companies seemingly taking longer to become listed and receiving more later stage investments (notably via secondary deals through platform such as SecondMarket), how much of their increase in value is extracted before they reach the listed markets?

Scrutiny on Performance

Morningstar has played an important role in making the fund management industry more transparent and it is no surprise to see it as an active investors in the financial services transparency field. MorningStar recently acquired HelloWallet for $52.5M and previously acquired ByAllAccounts for $28M (all transactions in 2014!)

While generic performance comparison has been more open for some time, how it applies to each person’s investments universe is a more recent trends. Companies such as Billguard are already providing antivirus-like services for your personal accounts. FeeX aims to do the same with managed portfolio fees. Looking beyond fees, startups such as Riskalyze can help identify the risk profile of each client and rate their current investments accordingly. Platforms such as Blueleaf (an Anthemis investment) drill down to each funds underlying assets to verify detailed exposure across a customer’s multiple investments. Both Riskalyze and Blueleaf are advisors focused, empowering financial advisors to provide more transparent performance to their customers.

Broken distribution?

The distribution of financial services is facing a major shift over the next years. As showed by Brett King, the traditional brick and mortars infrastructure is fading away.

Number of visits per month / year

Younger generation are less and less engaged with the physical distribution of financial services. In growing urban areas they are also less likely to engage in transactions that require branch interactions (mortgage etc). This leaves an opportunity for startups such as Betterment or Wealthfront to fill the void left by banks and traditional players. It is limiting to define these businesses as just online, their capacity to craft a digital experience in line with the expectations of the younger generations is unmatched by traditional financial services players.

Additionally we are seeing an evolution in investment behaviours of Millenials that potentially in conflict with traditional asset management:

Affluent millennials hold 52 percent of their money in cash and 28 percent in stocks, compared with 23 percent and 46 percent for older people, a UBS survey released in the first quarter found. The study focused on 21- to 29-year-olds with $75,000 in income or $50,000 in investable cash, and 30- to 36-year-olds with $100,000 in income or assets.

as the Blooomberg article explains:

“We call them Recession Babies,” said William Finnegan, a senior managing director at MFS Investment Management in Boston, drawing a parallel to “Depression Babies” who avoided banks and investing after the 1929 crash. “If the cumulative return of the past five years didn’t convince you that the stock market might be an OK place to be for a long-term investor, I’m not sure what else is going to. These folks have been scarred.”

I don’t think it is right to think Millenials are just risk averse. After all we are talking about people investing in crowdfunding platform such as Kickstarter and a generation expected to have shorter job tenures than previously. We may see an overall shift of having both a highly conservative and highly speculative risk profile, with little left in the middle.

However the Financial Advisors industry seems to be mostly focused on the current high value client base, mainly retirement focused. How many financial services company will follow Merril Lynch and name a director of financial gerontology?

Commoditization of Analysis

One of less talked about fundamental change on the analyst industry is the influence of the XBRL format (I wrote a first post on this topic in 2010: still valid imv: http://tekfin.com/2010/08/02/will-financial-information-become-the-next-commodity-data/). With the SEC making it mandatory for companies to report their accounts in machine readable format (include notes), performing core financial analysis and building baseline models will become a commodity. Trefis is a good example of how machine readable financial information can make model building different.

Additionally, with the improvement in distributed computing and AI, new models appears that are removing the pain from complex analysis. Companies such as Kensho with Warren makes complex correlation analysis a breeze (one of the most impressive demos I have seen recently). Signals are also becoming “free” with companies such as Estimize providing unique insights into Buy Side analysts expectation of stock performance, beating Wall Street analysts 69.5% of the time (now extending to economic forecasts and M&A deals).

In this new environment, how will asset managers differentiate and create above average returns? When more and more data becomes available, is information asymmetry gone as a differentiator? Is AmPro competition a growing threat? “Older” companies such as Covestor have been created on that basis and new competitors such as Motif also offer the opportunity for anyone to pick stocks and pitch their investment ideas. One of the main drivers of the new coming competition is in my view the lower transactions costs, new players coming out of the Robinhood (a zero fee broker) trading API will be interesting to follow.

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(This post has been long in the making). One of the posts that sparked my interest in the last months is a post by Chris Dixon, Full Stacked Startups. In it, Chris highlights several startups such as Nest, Uber, Tesla, Warby Parker as companies that have gone after the market as full-fledged businesses instead stacking on top or in partnership with other players. Notably the …

[…] full stack approach lets you bypass industry incumbents, completely control the customer experience, and capture a greater portion of the economic benefits you provide.

Recent transactions, such as Twitter’s acquisition of Gnip, are also showing, in my view, the business tension by any tech startups to move vertically upstream or downstream to find the right mix of economic models.

A system blueprint is a great way to start but is one of the views of a fractal of perspectives that needs to be taken when considering financial services (I highlighted in red what I think is one of the key area). Another important one is the financial view. A full stack financial services startups is, in my view, a balance sheet driven startup. Balance sheet driven startups are a bit of an exception in the world of technology startups. In the past years, a lot has been made to make these less and less driven by balance sheet. From renting infrastructure to outsourcing functionalities to other companies, most tech startups have been driven at first with little focus on balance sheet. However in the world of financial services whether banking or insurance, balance sheet driven startups are the default structure for full stack startups.

That makes them more difficult to be considered from a venture capital perspective:

– First, they require capital, much more than a typical tech startup. Oscar’s minimum capital requirement for operating as a health insurer in the state of New York is USD 45M : http://www.dfs.ny.gov/insurance/exam_rpt/x9475o13.pdf , most/all of which will need to be kept aside. That’s a $45M raise just for the right to play. Additional funds will be required for development, marketing, …

– Second, they are very difficult to grow hockey stick. Think of balance sheet driven financial services startups as the weird cousin of multi-sided marketplaces startups. Taking the example of a new bank, for every new customer that will subscribe and deposit, a matching capital will need to be added following Basel III or another local capital requirement rule, invested in secure products. In parallel, you will want to deploy your customers’ deposits in money-making investments with risk profiles compatible with your capital requirements. Either you run your own lending / investment business which adds further complexity or you look for partners to deploy. Low risk with relatively good returns investments are chased by investors and your new bank is a small fish in that pond. All of this contributes to make growth more difficult than in a typical startup.

Even for a simpler version of balance sheet driven startups, say a lender with little/no prudential ratio, every growth in customers will need to be matched with an increase in available capital. Kabbage debt raise is a good example of that: ~$53M raised in equity for ~$345M raised in debt.

So why are full stack financial services startups interesting?:

– From an operational point of view, these activities are enormously inefficient in existing banks. The software they are using (Core Banking Software) is old, batch based and difficult to replace – understandably, once you have built a full balance sheet, something that can affect its management is high risk. Anything build on top of this software base is affected, from your customer front end to your risk management software to your lending activities. This leads to more operational margins being taken to ensure you are operating within regulation. A new player will have tremendous opportunities using the flexibility that current software allows. I am playing our book here (Anthemis) but Fidor Bank‘s ability to connect to P2P lending platforms, virtual currency exchanges or to manage multicurrency /commodity accounts is a good example. This is an incredible opportunity space.

– From a business point of view, once you are past the more difficult early stage balance sheet growth phase, you have built a resilient, flexible company. Flexible is not an adjective often used for banks, but with the right infrastructure and API layers I think modern banks will have the opportunity to open themselves to many business models. Built in-house or in partnership with others. This is also the case in terms of their capability to deploy assets. Financial products, liquidity providers, exchanges are evolving at a rapid pace. New platforms appear to access private companies equities, alternative debts (P2P but also factoring, data driven SMB debt). Non banks are becoming investors as well, investing in their own supply chain to guarantee its performance. And these platforms are becoming more and more digital, creating new opportunities for a bank to connect and invest.

Note 3: This is also where the evolution around contracts in the blockchain such as Ethereum, or distributed open ledger such as Ripple (which recently partnered with Fidor Bank) are really important. Making transactions fully electronic and real-time has massive implications for banks in terms of their investments as well as their risk monitoring.

There are a lot of additional perspectives to consider and I will gladly take additional insights, critics, comments. However if you are working on building a full stack financial services startups, whether in banking or insurance, I am really interested in talking with you. There are very few now but I am betting we will see more and more people try in the coming years.

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Bill Ready had a great post at PandoDaily on the growing importance of smart mobile driven commerce. In my view this is one side of the equation of the future of commerce, the other side being the creation of smart banking services.

Using Bill’s example: I book a flight to San Francisco, my financial service app warns me that my travel budget will most likely be exceeded this month and has pushed back the budget allocation for new electronics by 1 month. My extra rental revenue from Airbnb should help cover cash flow needs for the month so that new MacBook is still a go. I take an Uber upon landing and check a restaurant for the group. Bills is split between us automatically, referring back to our positions in a global distributed ledger including interests owed (built on the Bitcoin protocol foundation). After the lunch, I check recent communications from my Angellist portfolio. My portfolio allocation to startups is split across various syndicates. Through tasks performed to help these startups, I have also earned additional exposure to a few. A good way to not only increase my upside potential but build my skills and experience.

Is this future far away? With the increase in sensors in mobile, shops, objects and the digitisation of money, the capabilities of financial services are changing quickly. A lot of this effort in calculation is currently focused on market activities (high frequency trading being probably the most discussed) but I am convinced we will see the same push start in consumer finance. The current push to integrate more data sources, including social data sources, in online lending is a good example.

Mobile is becoming an integral part of people’s financial life. Starbucks success with its mobile app proves that people, when given a good use case for mobile (increase in convenience and additional services) are more than ready to use their mobile. Payments on mobile are increasing at an amazing pace: Paypal’s total payment volume increased to $27 billions in 2013. But the increase in payments on mobile also highlights the gap between how easy it has become to spend online and how little has been done in helping people manage their spending.

Cash was the base budget management tool for a lot of people. A wallet is probably one of the best UX for money. Visually checking how much is left in a wallet is one of the most used and simple budget management tool. The rise of prepaid card with underbanked and neobanked is in some ways following the same trend, as closed cards, especially with easy to access mobile balance reminders, are the modern equivalent of counting the number of $10 left.

However, as highlighted above, as more and more of our purchase experience will not only shift to mobile online or offline but also to 1-click / no click payment, having a single credit card or debit card as a default payment mean can potentially increase the tensions in budget management and understanding of personal finance. In a world where payment is bound to disappear, the pressure for financial understanding will increase further.This is a vast opportunity for financial services startups.

The same technology that let applications recommend you what to purchase, how good a restaurant is or how to manage a fleet of cars / pricing to match demand can be used to optimize your personal financial management. As the age of mobile concierge is coming, the age of mobile financial advisors is coming as well. I am biased, professionally and personally on Simple but they are, in my view, a good example. Smart balance and goals are the beginning of a payment experience based around managing and optimising personal finance. And while this effort begins with spending, it will soon integrate as well with saving and borrowing. Paying overdraft fees with a saving account or other type of liquid assets is an incoherence in a time where a simple excel spreadsheet can compare borrowing and savings rates.

If we push this idea a little further, there is a potential for algorithmic finance becoming even more intelligent. We are on the verge of being able to record how people feel at any point in time. What about a financial algorithm that would help people maximize their happiness over time? What about a mobile agent that prevents you from buying stuff at checkout by automatically reminding of the other activities you would like to do that will be more rewarding?

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I have been a strong partisan of Banking as a Service and posted several times on the topic on this blog. Recently I have posted more on the shiny outer layers that could be / are created in such a stack but not so much of the core services under it. So it was with interest that I saw @giyom‘s tweet

A banking utility doesn’t buy debts, issue liabilities nor do maturity transformation, it only is a trusted accountant btw borrowers&debtors

It’s an interesting view, a pure banking utility would provide the pipes to connect depositors and borrowers and maintain the accounting trust between the two, whether direct, in a P2P lending type model, or indirect by reporting aggregated assets and loans. @giyom pointed me also to Dan Kaminsky analysis of Bitcoin: http://www.slideshare.net/dakami/bitcoin-8776098 – slide 14 and 15 are interesting in his analysis that supernodes in Bitcoin are effectively banks.

In parallel, a second French bank announced the launch of its API: AXA Banque (Credit Agricole was the first one with CAstore). I had the chance to talk with people there and while the current API is READ only, the mention of WRITE capabilities was not rejected from the outset. A Bank that proposes a READ/WRITE API is in effect giving up on a part of the their customer access and accepting its role as a utility for other services (as I pointed out before, it is something well know in the banking industry)

It seems that from both end of the spectrum, whether its is the technology enabled P2P or traditional Banking, we are moving toward the creation of banking utilities. But what would be the business model of such players?

On one hand, in the P2P lending example and as specified by giyom, the role of the core provider is track and ensure the relationships between borrowers and lender as well as provide additional services such as transparency in the capacities of the borrowers and loan recovery in the situation of a default. In this system, the trusted core providers would have no leverage nor insurance (as deposit accounts are currently protected). In theory, insurance could be provided by an external provider up to certain amount and based on the lenders selected. The business model of such a platform is fee based.

On the other hand, in a banking platform world, the bank uses the top layer as a deposits aggregators. It can provide non-interest bearing accounts and base interest bearing accounts the aggregator, as well as transaction facilities to help move money between various accounts. It provides the underlying regulated insurance to the end users. This source of deposits become a part of its core assets mix, which can be leveraged for lending. The same or other providers could be provided these lending facilities, with various rates based on risk etc.. The business model of such a platform is spread based.

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I have been a strong advocate of disruptive startups in Financial Services on this blog, dismissing some of the banks effort to try and move as quickly as more nimble competitors. But in all respect, for these innovative startups to launch their services, we need brilliant established banks and payments players. That is why I was surprised to read Finextra’s post Citi slaps down Bank 2.0 rivals in Innotribe face-off.

Banking is, as it should be, a highly regulated industry. After all, its all about money:

Money
It’s a crime
Share it fairly
But don’t take a slice of my pie
Money
So they say
Is the root of all evil today

Financial Services, to work in a global way also need a level of coordination only achieved through mature players and global coordination. Swift is a prime example. The Society for Worldwide Interbank Financial Telecommunication, is a cooperative owned by its members. It operates the pipes that allows banks to communicate with each other. The most known feature is probably payment, but other messages types are supported, from buying securities, to informing of the merger of 2 companies. In most of the world (the US being one exception). Swift is the common language of most financial institutions.

These skills (operating in a regulated environment, coordinating with different players) are very important, because without them, in the current environment, there can’t be any Banksimple, Wepay or Square. These Financial Services disruptors need a ground of base services (secure holding of funds, ability to communicate with other financial institutions) to propose innovative front-end solutions to their customers. There is no point in reinventing the wheel if you can find satisfactory services with a provider and focus on your core.

But this is where we need brilliant banks / financial institutions. Because what happens when they are not is a total disruptions of their business. The recent post of Kosta Peric, head of Innovation at SWIFT, comparing bank to bank payments and Paypal payments is a prime example: http://copernicc.wordpress.com/2011/09/26/money-transfer-experiment-chapter-1-paypal/. Paypal wins easily on the transfer of small amounts between countries.

It’s difficult, for some part of the financial services industry to realize that a winning strategy for them would be to become highly qualified service providers, top notch commodities. That there is a play in becoming the efficient platform of front end services, to be more like a water service company for a major city. I believe (or assume) that is what Citi has in mind when they announced the release of their B2B API: